System for predictive resource access within a technical environment

ABSTRACT

Systems, computer program products, and methods are described herein for predictive resource access within a technical environment. The present invention is configured to initiate a resource monitoring engine on a resource procurement profile associated with a user; receive information associated with one or more resources accessed by the user over a predetermined past period of time; receive information associated with one or more user characteristics associated with the user; initiate one or more machine learning algorithms on the one or more resources and the information associated with one or more user characteristics; generate, using the one or more machine learning algorithms, a forecasting model configured to predict one or more future resources accessible to the user at a predetermined future time; and initiate a resource transformation engine on the one or more future resources predicted to be accessible to the user at the predetermined future time.

FIELD OF THE INVENTION

The present invention embraces a system for predictive resource accesswithin a technical environment.

BACKGROUND

Predictive analytics is an application of artificial intelligence thatcan be used by entities to optimize their processes while reducing costand increasing efficiency of resource distribution and access.

There is a need for a system for predictive resource access within atechnical environment.

SUMMARY

The following presents a simplified summary of one or more embodimentsof the present invention, in order to provide a basic understanding ofsuch embodiments. This summary is not an extensive overview of allcontemplated embodiments, and is intended to neither identify key orcritical elements of all embodiments nor delineate the scope of any orall embodiments. Its sole purpose is to present some concepts of one ormore embodiments of the present invention in a simplified form as aprelude to the more detailed description that is presented later.

In one aspect, a system for predictive resource access within atechnical environment is presented. The system comprising: at least onenon-transitory storage device; and at least one processing devicecoupled to the at least one non-transitory storage device, wherein theat least one processing device is configured to: initiate a resourcemonitoring engine on a resource procurement profile associated with auser; electronically receive, using the resource monitoring engine,information associated with one or more resources accessed by the userover a predetermined past period of time; electronically receiveinformation associated with one or more user characteristics associatedwith the user; initiate one or more machine learning algorithms on theone or more resources and the information associated with one or moreuser characteristics; generate, using the one or more machine learningalgorithms, a forecasting model configured to predict one or more futureresources accessible to the user at a predetermined future time;initiate a resource transformation engine on the one or more futureresources predicted to be accessible to the user at the predeterminedfuture time; transform, using the resource transformation engine, theone or more future resources predicted to be accessible to the user atthe predetermined future time into one or more alternate resources,wherein the one or more alternate resources are immediately accessibleto the user; and transmit control signals configured to cause acomputing device of the user to display the one or more alternateresources immediately accessible to the user.

In some embodiments, the at least one processing device is furtherconfigured to: electronically receive, using the resource monitoringengine, the information associated with the one or more resources,wherein the information associated with the one or more resourcescomprises at least a resource type.

In some embodiments, the at least one processing device is furtherconfigured to: electronically receive information associated with theone or more user characteristics associated with the user, wherein theone or more user characteristics comprises at least one or more pastresource transfers executed by the user, a geographic location of theuser, a period amount of incoming funds, a periodic amount of outgoingfunds, spending behavior, and/or saving behavior.

In some embodiments, the at least one processing device is furtherconfigured to: determine a user authorization profile associated withthe user, wherein the user authorization profile comprises at least oneor more predetermined authorization profiles; and initiate the one ormore machine learning algorithms on the one or more resources, theinformation associated with one or more user characteristics, and theuser authorization profile.

In some embodiments, the at least one processing device is furtherconfigured to: electronically receive, via the computing device of theuser, one or more authorization attributes associated with the user;compare the one or more authorization attributes with the one or morepredetermined authorization profiles to determine a match; and determinethe user authorization profile based on at least determining the match.

In some embodiments, the one or more authorization attributes comprisesat least a punctuality associated with past resource transfers executedby the user, an amount of resource obligation, a type of resourceobligation, a number of resource procurement profiles associated withthe user, and/or a longevity of a relationship of the user with one ormore entities associated with the resource procurement profiles.

In some embodiments, the at least one processing device is furtherconfigured to: initiate the one or more machine learning algorithms,wherein the one or more machine learning algorithms comprises at leastone or more forecasting algorithms.

In some embodiments, the at least one processing device is furtherconfigured to: determine that the one or more future resources areassociated with a first resource type, wherein the first resource typeis not immediately accessible to the user; and initiate the resourcetransformation engine on the one or more future resources, wherein theresource transformation engine is configured to convert the one or morefuture resources from a first resource type to a second resource type,wherein the second resource type is immediately accessible to the user.

In another aspect, a computer program product for predictive resourceaccess within a technical environment is presented. The computer programproduct comprising a non-transitory computer-readable medium comprisingcode causing a first apparatus to: initiate a resource monitoring engineon a resource procurement profile associated with a user; electronicallyreceive, using the resource monitoring engine, information associatedwith one or more resources accessed by the user over a predeterminedpast period of time; electronically receive information associated withone or more user characteristics associated with the user; initiate oneor more machine learning algorithms on the one or more resources and theinformation associated with one or more user characteristics; generate,using the one or more machine learning algorithms, a forecasting modelconfigured to predict one or more future resources accessible to theuser at a predetermined future time; initiate a resource transformationengine on the one or more future resources predicted to be accessible tothe user at the predetermined future time; transform, using the resourcetransformation engine, the one or more future resources predicted to beaccessible to the user at the predetermined future time into one or morealternate resources, wherein the one or more alternate resources areimmediately accessible to the user; and transmit control signalsconfigured to cause a computing device of the user to display the one ormore alternate resources immediately accessible to the user.

In yet another aspect, a method for predictive resource access within atechnical environment is presented. The method comprising: initiating aresource monitoring engine on a resource procurement profile associatedwith a user; electronically receiving, using the resource monitoringengine, information associated with one or more resources accessed bythe user over a predetermined past period of time; electronicallyreceiving information associated with one or more user characteristicsassociated with the user; initiating one or more machine learningalgorithms on the one or more resources and the information associatedwith one or more user characteristics; generating, using the one or moremachine learning algorithms, a forecasting model configured to predictone or more future resources accessible to the user at a predeterminedfuture time; initiating a resource transformation engine on the one ormore future resources predicted to be accessible to the user at thepredetermined future time; transforming, using the resourcetransformation engine, the one or more future resources predicted to beaccessible to the user at the predetermined future time into one or morealternate resources, wherein the one or more alternate resources areimmediately accessible to the user; and transmitting control signalsconfigured to cause a computing device of the user to display the one ormore alternate resources immediately accessible to the user.

The features, functions, and advantages that have been discussed may beachieved independently in various embodiments of the present inventionor may be combined with yet other embodiments, further details of whichcan be seen with reference to the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Having thus described embodiments of the invention in general terms,reference will now be made the accompanying drawings, wherein:

FIG. 1 illustrates technical components of a system for predictiveresource access within a technical environment, in accordance with anembodiment of the invention; and

FIG. 2 illustrates a process flow for predictive resource access withina technical environment, in accordance with an embodiment of theinvention.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

Embodiments of the present invention will now be described more fullyhereinafter with reference to the accompanying drawings, in which some,but not all, embodiments of the invention are shown. Indeed, theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein; rather, theseembodiments are provided so that this disclosure will satisfy applicablelegal requirements. Where possible, any terms expressed in the singularform herein are meant to also include the plural form and vice versa,unless explicitly stated otherwise. Also, as used herein, the term “a”and/or “an” shall mean “one or more,” even though the phrase “one ormore” is also used herein. Furthermore, when it is said herein thatsomething is “based on” something else, it may be based on one or moreother things as well. In other words, unless expressly indicatedotherwise, as used herein “based on” means “based at least in part on”or “based at least partially on.” Like numbers refer to like elementsthroughout.

As used herein, an “entity” may be any institution employing informationtechnology resources and particularly technology infrastructureconfigured for processing large amounts of data. Typically, these datacan be related to the people who work for the organization, its productsor services, the customers or any other aspect of the operations of theorganization. As such, the entity may be any institution, group,association, financial institution, establishment, company, union,authority or the like, employing information technology resources forprocessing large amounts of data.

As described herein, a “user” may be an individual associated with anentity. As such, in some embodiments, the user may be an individualhaving past relationships, current relationships or potential futurerelationships with an entity. In some embodiments, a “user” may be anemployee (e.g., an associate, a project manager, an IT specialist, amanager, an administrator, an internal operations analyst, or the like)of the entity or enterprises affiliated with the entity, capable ofoperating the systems described herein. In some embodiments, a “user”may be any individual, entity or system who has a relationship with theentity, such as a customer or a prospective customer. In otherembodiments, a user may be a system performing one or more tasksdescribed herein.

As used herein, a “user interface” may be any device or software thatallows a user to input information, such as commands or data, into adevice, or that allows the device to output information to the user. Forexample, the user interface includes a graphical user interface (GUI) oran interface to input computer-executable instructions that direct aprocessing device to carry out specific functions. The user interfacetypically employs certain input and output devices to input datareceived from a user second user or output data to a user. These inputand output devices may include a display, mouse, keyboard, button,touchpad, touch screen, microphone, speaker, LED, light, joystick,switch, buzzer, bell, and/or other user input/output device forcommunicating with one or more users.

As used herein, an “engine” may refer to core elements of a computerprogram, or part of a computer program that serves as a foundation for alarger piece of software and drives the functionality of the software.An engine may be self-contained, but externally-controllable code thatencapsulates powerful logic designed to perform or execute a specifictype of function. In one aspect, an engine may be underlying source codethat establishes file hierarchy, input and output methods, and how aspecific part of a computer program interacts or communicates with othersoftware and/or hardware. The specific components of an engine may varybased on the needs of the specific computer program as part of thelarger piece of software. In some embodiments, an engine may beconfigured to retrieve resources created in other computer programs,which may then be ported into the engine for use during specificoperational aspects of the engine. An engine may be configurable to beimplemented within any general purpose computing system. In doing so,the engine may be configured to execute source code embedded therein tocontrol specific features of the general purpose computing system toexecute specific computing operations, thereby transforming the generalpurpose system into a specific purpose computing system.

As used herein, a “resource” may generally refer to objects, products,devices, goods, commodities, services, rewards, offers, discounts, andthe like, and/or the ability and opportunity to access and use the same.Some example implementations herein contemplate property held by a user,including property that is stored and/or maintained by a third-partyentity. In some example implementations, a resource may be associatedwith one or more accounts or may be property that is not associated witha specific account. Examples of resources associated with accounts maybe accounts that have cash or cash equivalents, commodities, and/oraccounts that are funded with or contain property, such as safetydeposit boxes containing jewelry, art or other valuables, a trustaccount that is funded with property, or the like.

As used herein, a “resource transfer” may refer to any transaction,activities or communication between one or more entities, or between theuser and the one or more entities. A resource transfer may refer to anydistribution of resources such as, but not limited to, a payment,processing of funds, purchase of goods or services, a return of goods orservices, a payment transaction, a credit transaction, or otherinteractions involving a user's resource or account. In the context ofan entity such as a financial institution, a resource transfer may referto one or more of: a sale of goods and/or services, initiating anautomated teller machine (ATM) or online banking session, an accountbalance inquiry, a rewards transfer, an account money transfer orwithdrawal, opening a bank application on a user's computer or mobiledevice, a user accessing their e-wallet, or any other interactioninvolving the user and/or the user's device that invokes or isdetectable by the financial institution. In some embodiments, the usermay authorize a resource transfer using at least a payment instrument(credit cards, debit cards, checks, digital wallets, currency, loyaltypoints), and/or payment credentials (account numbers, payment instrumentidentifiers). A resource transfer may include one or more of thefollowing: renting, selling, and/or leasing goods and/or services (e.g.,groceries, stamps, tickets, DVDs, vending machine items, and the like);making payments to creditors (e.g., paying monthly bills; payingfederal, state, and/or local taxes; and the like); sending remittances;loading money onto stored value cards (SVCs) and/or prepaid cards;donating to charities; and/or the like. Unless specifically limited bythe context, a “resource transfer” a “transaction”, “transaction event”or “point of transaction event” may refer to any activity between auser, a merchant, an entity, or any combination thereof. In someembodiments, a resource transfer or transaction may refer to financialtransactions involving direct or indirect movement of funds throughtraditional paper transaction processing systems (i.e. paper checkprocessing) or through electronic transaction processing systems. Inthis regard, resource transfers or transactions may refer to the userinitiating a purchase for a product, service, or the like from amerchant. Typical financial transactions include point of sale (POS)transactions, automated teller machine (ATM) transactions,person-to-person (P2P) transfers, internet transactions, onlineshopping, electronic funds transfers between accounts, transactions witha financial institution teller, personal checks, conducting purchasesusing loyalty/rewards points etc. When discussing that resourcetransfers or transactions are evaluated it could mean that thetransaction has already occurred, is in the process of occurring orbeing processed, or it has yet to be processed/posted by one or morefinancial institutions. In some embodiments, a resource transfer ortransaction may refer to non-financial activities of the user. In thisregard, the transaction may be a customer account event, such as but notlimited to the customer changing a password, ordering new checks, addingnew accounts, opening new accounts, adding or modifying accountparameters/restrictions, modifying a payee list associated with one ormore accounts, setting up automatic payments, performing/modifyingauthentication procedures and/or credentials, and the like.

As used herein, “payment instrument” may refer to an electronic paymentvehicle, such as an electronic credit or debit card. The paymentinstrument may not be a “card” at all and may instead be accountidentifying information stored electronically in a user device, such aspayment credentials or tokens/aliases associated with a digital wallet,or account identifiers stored by a mobile application. In accordancewith embodiments of the invention, the term “module” with respect to anapparatus may refer to a hardware component of the apparatus, a softwarecomponent of the apparatus, or a component of the apparatus thatcomprises both hardware and software. In accordance with embodiments ofthe invention, the term “chip” may refer to an integrated circuit, amicroprocessor, a system-on-a-chip, a microcontroller, or the like thatmay either be integrated into the external apparatus or may be insertedand removed from the external apparatus by a user.

As used herein, “authentication credentials” may be any information thatcan be used to identify of a user. For example, a system may prompt auser to enter authentication information such as a username, a password,a personal identification number (PIN), a passcode, biometricinformation (e.g., voice authentication, a fingerprint, and/or a retinascan), an answer to a security question, a unique intrinsic useractivity, such as making a predefined motion with a user device. Thisauthentication information may be used to authenticate the identity ofthe user (e.g., determine that the authentication information isassociated with the account) and determine that the user has authorityto access an account or system. In some embodiments, the system may beowned or operated by an entity. In such embodiments, the entity mayemploy additional computer systems, such as authentication servers, tovalidate and certify resources inputted by the plurality of users withinthe system. The system may further use its authentication servers tocertify the identity of users of the system, such that other users mayverify the identity of the certified users. In some embodiments, theentity may certify the identity of the users. Furthermore,authentication information or permission may be assigned to or requiredfrom a user, application, computing node, computing cluster, or the liketo access stored data within at least a portion of the system.

As used herein, an “interaction” may refer to any communication betweenone or more users, one or more entities or institutions, and/or one ormore devices, nodes, clusters, or systems within the system environmentdescribed herein. For example, an interaction may refer to a transfer ofdata between devices, an accessing of stored data by one or more nodesof a computing cluster, a transmission of a requested task, or the like.

FIG. 1 presents an exemplary block diagram of the system environment forpredictive resource access within a technical environment 100, inaccordance with an embodiment of the invention. FIG. 1 provides a uniquesystem that includes specialized servers and system communicably linkedacross a distributive network of nodes required to perform the functionsof the process flows described herein in accordance with embodiments ofthe present invention.

As illustrated, the system environment 100 includes a network 110, asystem 130, and a user input system 140. Also shown in FIG. 1 is a userof the user input system 140. The user input system 140 may be a mobiledevice or other non-mobile computing device. The user may be a personwho uses the user input system 140 to execute resource transfers usingone or more applications stored thereon. The one or more applicationsmay be configured to communicate with the system 130, execute atransaction, input information onto a user interface presented on theuser input system 140, or the like. The applications stored on the userinput system 140 and the system 130 may incorporate one or more parts ofany process flow described herein.

As shown in FIG. 1, the system 130, and the user input system 140 areeach operatively and selectively connected to the network 110, which mayinclude one or more separate networks. In addition, the network 110 mayinclude a telecommunication network, local area network (LAN), a widearea network (WAN), and/or a global area network (GAN), such as theInternet. It will also be understood that the network 110 may be secureand/or unsecure and may also include wireless and/or wired and/oroptical interconnection technology.

In some embodiments, the system 130 and the user input system 140 may beused to implement the processes described herein, including themobile-side and server-side processes for installing a computer programfrom a mobile device to a computer, in accordance with an embodiment ofthe present invention. The system 130 is intended to represent variousforms of digital computers, such as laptops, desktops, workstations,personal digital assistants, servers, blade servers, mainframes, andother appropriate computers. The user input system 140 is intended torepresent various forms of mobile devices, such as personal digitalassistants, cellular telephones, smartphones, and other similarcomputing devices. The components shown here, their connections andrelationships, and their functions, are meant to be exemplary only, andare not meant to limit implementations of the inventions describedand/or claimed in this document.

In accordance with some embodiments, the system 130 may include aprocessor 102, memory 104, a storage device 106, a high-speed interface108 connecting to memory 104, and a low-speed interface 112 connectingto low speed bus 114 and storage device 106. Each of the components 102,104, 106, 108, 111, and 112 are interconnected using various buses, andmay be mounted on a common motherboard or in other manners asappropriate. The processor 102 can process instructions for executionwithin the system 130, including instructions stored in the memory 104or on the storage device 106 to display graphical information for a GUIon an external input/output device, such as display 116 coupled to ahigh-speed interface 108. In other implementations, multiple processorsand/or multiple buses may be used, as appropriate, along with multiplememories and types of memory. Also, multiple systems, same or similar tosystem 130 may be connected, with each system providing portions of thenecessary operations (e.g., as a server bank, a group of blade servers,or a multi-processor system). In some embodiments, the system 130 may bea server managed by the business. The system 130 may be located at thefacility associated with the business or remotely from the facilityassociated with the business.

The memory 104 stores information within the system 130. In oneimplementation, the memory 104 is a volatile memory unit or units, suchas volatile random access memory (RAM) having a cache area for thetemporary storage of information. In another implementation, the memory104 is a non-volatile memory unit or units. The memory 104 may also beanother form of computer-readable medium, such as a magnetic or opticaldisk, which may be embedded and/or may be removable. The non-volatilememory may additionally or alternatively include an EEPROM, flashmemory, and/or the like. The memory 104 may store any one or more ofpieces of information and data used by the system in which it resides toimplement the functions of that system. In this regard, the system maydynamically utilize the volatile memory over the non-volatile memory bystoring multiple pieces of information in the volatile memory, therebyreducing the load on the system and increasing the processing speed.

The storage device 106 is capable of providing mass storage for thesystem 130. In one aspect, the storage device 106 may be or contain acomputer-readable medium, such as a floppy disk device, a hard diskdevice, an optical disk device, or a tape device, a flash memory orother similar solid state memory device, or an array of devices,including devices in a storage area network or other configurations. Acomputer program product can be tangibly embodied in an informationcarrier. The computer program product may also contain instructionsthat, when executed, perform one or more methods, such as thosedescribed above. The information carrier may be a non-transitorycomputer- or machine-readable storage medium, such as the memory 104,the storage device 104, or memory on processor 102.

In some embodiments, the system 130 may be configured to access, via the110, a number of other computing devices (not shown). In this regard,the system 130 may be configured to access one or more storage devicesand/or one or more memory devices associated with each of the othercomputing devices. In this way, the system 130 may implement dynamicallocation and de-allocation of local memory resources among multiplecomputing devices in a parallel or distributed system. Given a group ofcomputing devices and a collection of interconnected local memorydevices, the fragmentation of memory resources is rendered irrelevant byconfiguring the system 130 to dynamically allocate memory based onavailability of memory either locally, or in any of the other computingdevices accessible via the network. In effect, it appears as though thememory is being allocated from a central pool of memory, even though thespace is distributed throughout the system. This method of dynamicallyallocating memory provides increased flexibility when the data sizechanges during the lifetime of an application, and allows memory reusefor better utilization of the memory resources when the data sizes arelarge.

The high-speed interface 108 manages bandwidth-intensive operations forthe system 130, while the low speed controller 112 manages lowerbandwidth-intensive operations. Such allocation of functions isexemplary only. In some embodiments, the high-speed interface 108 iscoupled to memory 104, display 116 (e.g., through a graphics processoror accelerator), and to high-speed expansion ports 111, which may acceptvarious expansion cards (not shown). In such an implementation,low-speed controller 112 is coupled to storage device 106 and low-speedexpansion port 114. The low-speed expansion port 114, which may includevarious communication ports (e.g., USB, Bluetooth, Ethernet, wirelessEthernet), may be coupled to one or more input/output devices, such as akeyboard, a pointing device, a scanner, or a networking device such as aswitch or router, e.g., through a network adapter.

The system 130 may be implemented in a number of different forms, asshown in FIG. 1. For example, it may be implemented as a standardserver, or multiple times in a group of such servers. Additionally, thesystem 130 may also be implemented as part of a rack server system or apersonal computer such as a laptop computer. Alternatively, componentsfrom system 130 may be combined with one or more other same or similarsystems and an entire system 140 may be made up of multiple computingdevices communicating with each other.

FIG. 1 also illustrates a user input system 140, in accordance with anembodiment of the invention. The user input system 140 includes aprocessor 152, memory 154, an input/output device such as a display 156,a communication interface 158, and a transceiver 160, among othercomponents. The user input system 140 may also be provided with astorage device, such as a microdrive or other device, to provideadditional storage. Each of the components 152, 154, 158, and 160, areinterconnected using various buses, and several of the components may bemounted on a common motherboard or in other manners as appropriate.

The processor 152 is configured to execute instructions within the userinput system 140, including instructions stored in the memory 154. Theprocessor may be implemented as a chipset of chips that include separateand multiple analog and digital processors. The processor may beconfigured to provide, for example, for coordination of the othercomponents of the user input system 140, such as control of userinterfaces, applications run by user input system 140, and wirelesscommunication by user input system 140.

The processor 152 may be configured to communicate with the user throughcontrol interface 164 and display interface 166 coupled to a display156. The display 156 may be, for example, a TFT LCD(Thin-Film-Transistor Liquid Crystal Display) or an OLED (Organic LightEmitting Diode) display, or other appropriate display technology. Thedisplay interface 156 may comprise appropriate circuitry and configuredfor driving the display 156 to present graphical and other informationto a user. The control interface 164 may receive commands from a userand convert them for submission to the processor 152. In addition, anexternal interface 168 may be provided in communication with processor152, so as to enable near area communication of user input system 140with other devices. External interface 168 may provide, for example, forwired communication in some implementations, or for wirelesscommunication in other implementations, and multiple interfaces may alsobe used.

The memory 154 stores information within the user input system 140. Thememory 154 can be implemented as one or more of a computer-readablemedium or media, a volatile memory unit or units, or a non-volatilememory unit or units. Expansion memory may also be provided andconnected to user input system 140 through an expansion interface (notshown), which may include, for example, a SIMM (Single In Line MemoryModule) card interface. Such expansion memory may provide extra storagespace for user input system 140, or may also store applications or otherinformation therein. In some embodiments, expansion memory may includeinstructions to carry out or supplement the processes described above,and may include secure information also. For example, expansion memorymay be provided as a security module for user input system 140, and maybe programmed with instructions that permit secure use of user inputsystem 140. In addition, secure applications may be provided via theSIMM cards, along with additional information, such as placingidentifying information on the SIMM card in a non-hackable manner. Insome embodiments, the user may use the applications to execute processesdescribed with respect to the process flows described herein.Specifically, the application executes the process flows describedherein. It will be understood that the one or more applications storedin the system 130 and/or the user computing system 140 may interact withone another and may be configured to implement any one or more portionsof the various user interfaces and/or process flow described herein.

The memory 154 may include, for example, flash memory and/or NVRAMmemory. In one aspect, a computer program product is tangibly embodiedin an information carrier. The computer program product containsinstructions that, when executed, perform one or more methods, such asthose described herein. The information carrier is a computer- ormachine-readable medium, such as the memory 154, expansion memory,memory on processor 152, or a propagated signal that may be received,for example, over transceiver 160 or external interface 168.

In some embodiments, the user may use the user input system 140 totransmit and/or receive information or commands to and from the system130. In this regard, the system 130 may be configured to establish acommunication link with the user input system 140, whereby thecommunication link establishes a data channel (wired or wireless) tofacilitate the transfer of data between the user input system 140 andthe system 130. In doing so, the system 130 may be configured to accessone or more aspects of the user input system 140, such as, a GPS device,an image capturing component (e.g., camera), a microphone, a speaker, orthe like.

The user input system 140 may communicate with the system 130 (and oneor more other devices) wirelessly through communication interface 158,which may include digital signal processing circuitry where necessary.Communication interface 158 may provide for communications under variousmodes or protocols, such as GSM voice calls, SMS, EMS, or MMS messaging,CDMA, TDMA, PDC, WCDMA, CDMA2000, or GPRS, among others. Suchcommunication may occur, for example, through radio-frequencytransceiver 160. In addition, short-range communication may occur, suchas using a Bluetooth, Wi-Fi, or other such transceiver (not shown). Inaddition, GPS (Global Positioning System) receiver module 170 mayprovide additional navigation- and location-related wireless data touser input system 140, which may be used as appropriate by applicationsrunning thereon, and in some embodiments, one or more applicationsoperating on the system 130.

The user input system 140 may also communicate audibly using audio codec162, which may receive spoken information from a user and convert it tousable digital information. Audio codec 162 may likewise generateaudible sound for a user, such as through a speaker, e.g., in a handsetof user input system 140. Such sound may include sound from voicetelephone calls, may include recorded sound (e.g., voice messages, musicfiles, etc.) and may also include sound generated by one or moreapplications operating on the user input system 140, and in someembodiments, one or more applications operating on the system 130.

Various implementations of the systems and techniques described here canbe realized in digital electronic circuitry, integrated circuitry,specially designed ASICs (application specific integrated circuits),computer hardware, firmware, software, and/or combinations thereof.These various implementations can include implementation in one or morecomputer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms “machine-readable medium”“computer-readable medium” refers to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,Programmable Logic Devices (PLDs)) used to provide machine instructionsand/or data to a programmable processor, including a machine-readablemedium that receives machine instructions as a machine-readable signal.The term “machine-readable signal” refers to any signal used to providemachine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniquesdescribed here can be implemented on a computer having a display device(e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor)for displaying information to the user and a keyboard and a pointingdevice (e.g., a mouse or a trackball) by which the user can provideinput to the computer. Other kinds of devices can be used to provide forinteraction with a user as well; for example, feedback provided to theuser can be any form of sensory feedback (e.g., visual feedback,auditory feedback, or tactile feedback); and input from the user can bereceived in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in acomputing system that includes a back end component (e.g., as a dataserver), or that includes a middleware component (e.g., an applicationserver), or that includes a front end component (e.g., a client computerhaving a graphical user interface or a Web browser through which a usercan interact with an implementation of the systems and techniquesdescribed here), or any combination of such back end, middleware, orfront end components. The components of the system can be interconnectedby any form or medium of digital data communication (e.g., acommunication network). Examples of communication networks include alocal area network (“LAN”), a wide area network (“WAN”), and theInternet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

It will be understood that the embodiment of the system environmentillustrated in FIG. 1 is exemplary and that other embodiments may vary.As another example, in some embodiments, the system 130 includes more,less, or different components. As another example, in some embodiments,some or all of the portions of the system environment 100 may becombined into a single portion. Likewise, in some embodiments, some orall of the portions of the system 130 may be separated into two or moredistinct portions.

FIG. 2 illustrates a process flow for predictive resource access withina technical environment 200, in accordance with an embodiment of theinvention. As shown in block 202, the process flow includes initiating aresource monitoring engine on a resource procurement profile associatedwith a user.

Next, as shown in block 204, the process flow includes electronicallyreceiving, using the resource monitoring engine, information associatedwith one or more resources accessed by the user over a predeterminedpast period of time. In some embodiments, the resources accessed by theuser over the predetermined past period of time continue to remainavailable and accessible to the user. As described herein, the resourcesmay be associated with one or more financial products and/or servicesused by the user. In one example, the resources may be rewards fundsaccrued by the user in using a payment instrument associated with theentity. In some embodiments, the information associated with theresources may include a resource type. Following from the previousexample, if the resources accessed by the user is rewards funds accruedover the predetermined past period of time, the resource type mayindicate the type of rewards funds accessed by the user, such as, creditcard rewards, loyalty points, airline miles, discounts, offers, and/orthe like.

Next, as shown in block 206, the process flow includes electronicallyreceiving information associated with one or more user characteristicsassociated with the user. In some embodiments, the one or more usercharacteristics may include at least one or more past resource transfersexecuted by the user, a geographic location of the user, a period amountof incoming funds, a periodic amount of outgoing funds, spendingbehavior, saving behavior, and/or the like.

In some embodiments, the user characteristics may include a userauthorization profile. In one aspect, an authorization profile may referto profiles created for specific users based on user authorizationattributes. In one aspect, the one or more authorization attributes mayinclude, at least a punctuality associated with past resource transfersexecuted by the user, an amount of resource obligation, a type ofresource obligation, a number of resource procurement profilesassociated with the user, and/or a longevity of a relationship of theuser with one or more entities associated with the resource procurementprofiles. Accordingly, the system may be configured to electronicallyreceive, via the computing device of the user, one or more authorizationattributes associated with the user. In response to receiving the one ormore authorization attributes, the system may be configured to comparethe one or more authorization attributes with the one or morepredetermined authorization profiles to determine a match. In response,the system may be configured to determine the user authorization profilebased on at least determining the match.

In some embodiments, the user authorization profile may dictate theresources (e.g., future resources) that may be available and/oraccessible to the user. Accordingly, when the user wishes to access aresource located within a distributed network of servers, the system maybe configured to retrieve the authorization profile of the user andcompare the authorization profile with pre-configured rules specific tothe distributed network of servers to determine whether the one or moreauthorization attributes associated with the authorization profile ofthe user meets the requirements of the pre-configured rules. Based onthe comparison, the system may be configured to determine that the oneor more authorization attributes associated with the authorizationprofile of the user meets the requirements of the pre-configured rules.If so, the system may be configured to enable the user to access theresource within the distributed network of servers.

Next, as shown in block 208, the process flow includes initiating one ormore machine learning algorithms on the one or more resources and theinformation associated with one or more user characteristics. In someembodiments, the system may be configured to implement any of thefollowing applicable machine learning algorithms either singly or incombination: supervised learning (e.g., using logistic regression, usingback propagation neural networks, using random forests, decision trees,etc.), unsupervised learning (e.g., using an Apriori algorithm, usingK-means clustering), semi-supervised learning, reinforcement learning(e.g., using a Q-learning algorithm, using temporal differencelearning), and any other suitable learning style. Each module of theplurality can implement any one or more of: a regression algorithm(e.g., ordinary least squares, logistic regression, stepwise regression,multivariate adaptive regression splines, locally estimated scatterplotsmoothing, etc.), an instance-based method (e.g., k-nearest neighbor,learning vector quantization, self-organizing map, etc.), aregularization method (e.g., ridge regression, least absolute shrinkageand selection operator, elastic net, etc.), a decision tree learningmethod (e.g., classification and regression tree, iterative dichotomiser3, C4.5, chi-squared automatic interaction detection, decision stump,random forest, multivariate adaptive regression splines, gradientboosting machines, etc.), a Bayesian method (e.g., naïve Bayes, averagedone-dependence estimators, Bayesian belief network, etc.), a kernelmethod (e.g., a support vector machine, a radial basis function, alinear discriminate analysis, etc.), a clustering method (e.g., k-meansclustering, expectation maximization, etc.), an associated rule learningalgorithm (e.g., an Apriori algorithm, an Eclat algorithm, etc.), anartificial neural network model (e.g., a Perceptron method, aback-propagation method, a Hopfield network method, a self-organizingmap method, a learning vector quantization method, etc.), a deeplearning algorithm (e.g., a restricted Boltzmann machine, a deep beliefnetwork method, a convolution network method, a stacked auto-encodermethod, etc.), a dimensionality reduction method (e.g., principalcomponent analysis, partial least squares regression, Sammon mapping,multidimensional scaling, projection pursuit, etc.), an ensemble method(e.g., boosting, bootstrapped aggregation, AdaBoost, stackedgeneralization, gradient boosting machine method, random forest method,etc.), and any suitable form of machine learning algorithm. Eachprocessing portion of the system 100 can additionally or alternativelyleverage: a probabilistic module, heuristic module, deterministicmodule, or any other suitable module leveraging any other suitablecomputation method, machine learning method or combination thereof.However, any suitable machine learning approach can otherwise beincorporated in the system 100. Further, any suitable model (e.g.,machine learning, non-machine learning, etc.) can be used in generatingdata relevant to the system 130. In some embodiments, the one or moremachine learning algorithms may be predictive modeling algorithmsconfigured to use data and statistics to predict outcomes withforecasting models.

Next, as shown in block 210, the process flow includes generating, usingthe one or more machine learning algorithms, a forecasting modelconfigured to predict one or more future resources accessible to theuser at a predetermined future time. In some embodiments, theforecasting model may be generated by training on the informationassociated with one or more resources accessed by the user over apredetermined past period of time and information associated with theone or more user characteristics, including the user authorizationprofile. In doing so, the system may be configured to determine which ofthe future resources will be available to the user, and which of thoseavailable future resources will be accessible for the user. For example,the forecasting model may predict that only a subset of financialproducts and/or services may be available to the user. In some otherembodiments, the system may be configured to determine that all thefuture resources will be available to the user, but determine which ofthose future resources will be accessible for the user. For example, theforecasting model may predict that all the financial products and/orservices are available to the user, but the user is eligible to accessonly a subset of the financial products and/or services at thepredetermined future time. It is possible that in time, the number offinancial products and/or services are accessible for the user willincrease. In some embodiments, the one or more machine learningalgorithms may be used to calculate the probability that the one or morefuture resources will be available for the user, and the probabilitythat a particular future resource will be available to the user and theprobability that the user will be capable of accessing them at thepredetermined future time.

In some embodiments, the one or more future resources that aredetermined to be available and accessible for the user at thepredetermined future time are resources having pre-configured ruleswhose requirements are still met by the existing authorization profileof the user. In some other embodiments, the one or more future resourcesthat are determined to be available and/or accessible for the user atthe predetermined future time are resources having pre-configured ruleswhose requirements are not met by the existing authorization profile ofthe user. In such cases, the system may be configured to predict, usingthe forecasting model, one or more additional authorization attributesthat the user will have to acquire to meet the pre-configured rulesassociated with the future resources to make the future resourcesavailable and/or accessible for the user at the predetermined futuredate.

Next, as shown in block 212, the process flow includes initiating aresource transformation engine on the one or more future resourcespredicted to be accessible to the user at the predetermined future time.In some embodiments, the system may be configured to determine that theone or more future resources are not immediately accessible to the user(it remains accessible at the predetermined future date). In response,the system may be configured to initiate the resource transformationengine on the one or more future resources to transform the one or morefuture resources to enable the one or more future resources to becomeimmediately accessible to the user.

Next, as shown in block 214, the process flow includes transforming,using the resource transformation engine, the one or more futureresources predicted to be accessible to the user at the predeterminedfuture time into one or more alternate resources. In one aspect, the oneor more alternate resources are immediately accessible to the user. Forexample, assume that the one or more future resources are rewards fundsthe user is predicted to have accrued at the predetermined future timebased on the amount of rewards funds the user has accrued in the past.These rewards funds may be transformed into an alternate resource suchas a loan capable of being accessed by the user for immediate use, andavailable to be paid off by the rewards funds that are predicted for theuser to accrue until the predetermined future date.

In some embodiments, the system may be configured to determine that theone or more future resources are associated with a first resource typethat is not immediately accessible to the user. In response, the systemmay be configured to initiate the resource transformation engine on theone or more future resources associated with the first resource type, tobe transformed into a second resource type that is immediatelyaccessible to the user. Following from the previous example, assume thatthe amount of rewards funds the user is predicted to have accrued at thepredetermined future time is based on credit card usage (first resourcetype). These rewards funds may be transformed into an amount of fundsthat can be applied towards a specific merchant available immediatelyfor the user (second resource type).

In some embodiments, the system may be configured to determine thatwhile the authorization profile of the user will likely advance to apoint at the predetermined future date to meet the requirements ofaccessibility of the future resources, the current authorization profileof the user does not meet the requirements. Accordingly, the system maybe configured to determine the alternate resources that may be a portionof the one or more future resources that are capable of being accessedby the user immediately based on the user's current authorizationprofile.

Next, as shown in block 216, the process flow includes transmittingcontrol signals configured to cause a computing device of the user todisplay the one or more alternate resources immediately accessible tothe user. In this regard, the system may be configured to initiate apresentation of a user interface configured to display the one or morealternate resources to the user. In response, the user may select atleast one of the one or more alternate resources for access.

As will be appreciated by one of ordinary skill in the art in view ofthis disclosure, the present invention may include and/or be embodied asan apparatus (including, for example, a system, machine, device,computer program product, and/or the like), as a method (including, forexample, a business method, computer-implemented process, and/or thelike), or as any combination of the foregoing. Accordingly, embodimentsof the present invention may take the form of an entirely businessmethod embodiment, an entirely software embodiment (including firmware,resident software, micro-code, stored procedures in a database, or thelike), an entirely hardware embodiment, or an embodiment combiningbusiness method, software, and hardware aspects that may generally bereferred to herein as a “system.” Furthermore, embodiments of thepresent invention may take the form of a computer program product thatincludes a computer-readable storage medium having one or morecomputer-executable program code portions stored therein. As usedherein, a processor, which may include one or more processors, may be“configured to” perform a certain function in a variety of ways,including, for example, by having one or more general-purpose circuitsperform the function by executing one or more computer-executableprogram code portions embodied in a computer-readable medium, and/or byhaving one or more application-specific circuits perform the function.

It will be understood that any suitable computer-readable medium may beutilized. The computer-readable medium may include, but is not limitedto, a non-transitory computer-readable medium, such as a tangibleelectronic, magnetic, optical, electromagnetic, infrared, and/orsemiconductor system, device, and/or other apparatus. For example, insome embodiments, the non-transitory computer-readable medium includes atangible medium such as a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), a compact discread-only memory (CD-ROM), and/or some other tangible optical and/ormagnetic storage device. In other embodiments of the present invention,however, the computer-readable medium may be transitory, such as, forexample, a propagation signal including computer-executable program codeportions embodied therein.

One or more computer-executable program code portions for carrying outoperations of the present invention may include object-oriented,scripted, and/or unscripted programming languages, such as, for example,Java, Perl, Smalltalk, C++, SAS, SQL, Python, Objective C, JavaScript,and/or the like. In some embodiments, the one or morecomputer-executable program code portions for carrying out operations ofembodiments of the present invention are written in conventionalprocedural programming languages, such as the “C” programming languagesand/or similar programming languages. The computer program code mayalternatively or additionally be written in one or more multi-paradigmprogramming languages, such as, for example, F#.

Some embodiments of the present invention are described herein withreference to flowchart illustrations and/or block diagrams of apparatusand/or methods. It will be understood that each block included in theflowchart illustrations and/or block diagrams, and/or combinations ofblocks included in the flowchart illustrations and/or block diagrams,may be implemented by one or more computer-executable program codeportions. These one or more computer-executable program code portionsmay be provided to a processor of a general purpose computer, specialpurpose computer, and/or some other programmable data processingapparatus in order to produce a particular machine, such that the one ormore computer-executable program code portions, which execute via theprocessor of the computer and/or other programmable data processingapparatus, create mechanisms for implementing the steps and/or functionsrepresented by the flowchart(s) and/or block diagram block(s).

The one or more computer-executable program code portions may be storedin a transitory and/or non-transitory computer-readable medium (e.g. amemory) that can direct, instruct, and/or cause a computer and/or otherprogrammable data processing apparatus to function in a particularmanner, such that the computer-executable program code portions storedin the computer-readable medium produce an article of manufactureincluding instruction mechanisms which implement the steps and/orfunctions specified in the flowchart(s) and/or block diagram block(s).

The one or more computer-executable program code portions may also beloaded onto a computer and/or other programmable data processingapparatus to cause a series of operational steps to be performed on thecomputer and/or other programmable apparatus. In some embodiments, thisproduces a computer-implemented process such that the one or morecomputer-executable program code portions which execute on the computerand/or other programmable apparatus provide operational steps toimplement the steps specified in the flowchart(s) and/or the functionsspecified in the block diagram block(s). Alternatively,computer-implemented steps may be combined with, and/or replaced with,operator- and/or human-implemented steps in order to carry out anembodiment of the present invention.

Although many embodiments of the present invention have just beendescribed above, the present invention may be embodied in many differentforms and should not be construed as limited to the embodiments setforth herein; rather, these embodiments are provided so that thisdisclosure will satisfy applicable legal requirements. Also, it will beunderstood that, where possible, any of the advantages, features,functions, devices, and/or operational aspects of any of the embodimentsof the present invention described and/or contemplated herein may beincluded in any of the other embodiments of the present inventiondescribed and/or contemplated herein, and/or vice versa. In addition,where possible, any terms expressed in the singular form herein aremeant to also include the plural form and/or vice versa, unlessexplicitly stated otherwise. Accordingly, the terms “a” and/or “an”shall mean “one or more,” even though the phrase “one or more” is alsoused herein. Like numbers refer to like elements throughout.

While certain exemplary embodiments have been described and shown in theaccompanying drawings, it is to be understood that such embodiments aremerely illustrative of and not restrictive on the broad invention, andthat this invention not be limited to the specific constructions andarrangements shown and described, since various other changes,combinations, omissions, modifications and substitutions, in addition tothose set forth in the above paragraphs, are possible. Those skilled inthe art will appreciate that various adaptations, modifications, andcombinations of the just described embodiments can be configured withoutdeparting from the scope and spirit of the invention. Therefore, it isto be understood that, within the scope of the appended claims, theinvention may be practiced other than as specifically described herein.

What is claimed is:
 1. A system for predictive resource access within atechnical environment, the system comprising: at least onenon-transitory storage device; and at least one processing devicecoupled to the at least one non-transitory storage device, wherein theat least one processing device is configured to: initiate a resourcemonitoring engine on a resource procurement profile associated with auser; electronically receive, using the resource monitoring engine,information associated with one or more resources accessed by the userover a predetermined past period of time; electronically receiveinformation associated with one or more user characteristics associatedwith the user; initiate one or more machine learning algorithms on theone or more resources and the information associated with one or moreuser characteristics; generate, using the one or more machine learningalgorithms, a forecasting model configured to predict one or more futureresources accessible to the user at a predetermined future time;initiate a resource transformation engine on the one or more futureresources predicted to be accessible to the user at the predeterminedfuture time; transform, using the resource transformation engine, theone or more future resources predicted to be accessible to the user atthe predetermined future time into one or more alternate resources,wherein the one or more alternate resources are immediately accessibleto the user; and transmit control signals configured to cause acomputing device of the user to display the one or more alternateresources immediately accessible to the user.
 2. The system of claim 1,wherein the at least one processing device is further configured to:electronically receive, using the resource monitoring engine, theinformation associated with the one or more resources, wherein theinformation associated with the one or more resources comprises at leasta resource type.
 3. The system of claim 1, wherein the at least oneprocessing device is further configured to: electronically receiveinformation associated with the one or more user characteristicsassociated with the user, wherein the one or more user characteristicscomprises at least one or more past resource transfers executed by theuser, a geographic location of the user, a period amount of incomingfunds, a periodic amount of outgoing funds, spending behavior, and/orsaving behavior.
 4. The system of claim 1, wherein the at least oneprocessing device is further configured to: determine a userauthorization profile associated with the user, wherein the userauthorization profile comprises at least one or more predeterminedauthorization profiles; and initiate the one or more machine learningalgorithms on the one or more resources, the information associated withone or more user characteristics, and the user authorization profile. 5.The system of claim 4, wherein the at least one processing device isfurther configured to: electronically receive, via the computing deviceof the user, one or more authorization attributes associated with theuser; compare the one or more authorization attributes with the one ormore predetermined authorization profiles to determine a match; anddetermine the user authorization profile based on at least determiningthe match.
 6. The system of claim 5, wherein the one or moreauthorization attributes comprises at least a punctuality associatedwith past resource transfers executed by the user, an amount of resourceobligation, a type of resource obligation, a number of resourceprocurement profiles associated with the user, and/or a longevity of arelationship of the user with one or more entities associated with theresource procurement profiles.
 7. The system of claim 1, wherein the atleast one processing device is further configured to: initiate the oneor more machine learning algorithms, wherein the one or more machinelearning algorithms comprises at least one or more forecastingalgorithms.
 8. The system of claim 1, wherein the at least oneprocessing device is further configured to: determine that the one ormore future resources are associated with a first resource type, whereinthe first resource type is not immediately accessible to the user; andinitiate the resource transformation engine on the one or more futureresources, wherein the resource transformation engine is configured toconvert the one or more future resources from a first resource type to asecond resource type, wherein the second resource type is immediatelyaccessible to the user.
 9. A computer program product for predictiveresource access within a technical environment, the computer programproduct comprising a non-transitory computer-readable medium comprisingcode causing a first apparatus to: initiate a resource monitoring engineon a resource procurement profile associated with a user; electronicallyreceive, using the resource monitoring engine, information associatedwith one or more resources accessed by the user over a predeterminedpast period of time; electronically receive information associated withone or more user characteristics associated with the user; initiate oneor more machine learning algorithms on the one or more resources and theinformation associated with one or more user characteristics; generate,using the one or more machine learning algorithms, a forecasting modelconfigured to predict one or more future resources accessible to theuser at a predetermined future time; initiate a resource transformationengine on the one or more future resources predicted to be accessible tothe user at the predetermined future time; transform, using the resourcetransformation engine, the one or more future resources predicted to beaccessible to the user at the predetermined future time into one or morealternate resources, wherein the one or more alternate resources areimmediately accessible to the user; and transmit control signalsconfigured to cause a computing device of the user to display the one ormore alternate resources immediately accessible to the user.
 10. Thecomputer program product of claim 9, wherein the first apparatus isfurther configured to: electronically receive, using the resourcemonitoring engine, the information associated with the one or moreresources, wherein the information associated with the one or moreresources comprises at least a resource type.
 11. The computer programproduct of claim 9, wherein the first apparatus is further configuredto: electronically receive information associated with the one or moreuser characteristics associated with the user, wherein the one or moreuser characteristics comprises at least one or more past resourcetransfers executed by the user, a geographic location of the user, aperiod amount of incoming funds, a periodic amount of outgoing funds,spending behavior, and/or saving behavior.
 12. The computer programproduct of claim 9, wherein the first apparatus is further configuredto: determine a user authorization profile associated with the user,wherein the user authorization profile comprises at least one or morepredetermined authorization profiles; and initiate the one or moremachine learning algorithms on the one or more resources, theinformation associated with one or more user characteristics, and theuser authorization profile.
 13. The computer program product of claim12, wherein the first apparatus is further configured to: electronicallyreceive, via the computing device of the user, one or more authorizationattributes associated with the user; compare the one or moreauthorization attributes with the one or more predeterminedauthorization profiles to determine a match; and determine the userauthorization profile based on at least determining the match.
 14. Thecomputer program product of claim 13, wherein the one or moreauthorization attributes comprises at least a punctuality associatedwith past resource transfers executed by the user, an amount of resourceobligation, a type of resource obligation, a number of resourceprocurement profiles associated with the user, and/or a longevity of arelationship of the user with one or more entities associated with theresource procurement profiles.
 15. The computer program product of claim9, wherein the first apparatus is further configured to: initiate theone or more machine learning algorithms, wherein the one or more machinelearning algorithms comprises at least one or more forecastingalgorithms.
 16. The computer program product of claim 9, wherein thefirst apparatus is further configured to: determine that the one or morefuture resources are associated with a first resource type, wherein thefirst resource type is not immediately accessible to the user; andinitiate the resource transformation engine on the one or more futureresources, wherein the resource transformation engine is configured toconvert the one or more future resources from a first resource type to asecond resource type, wherein the second resource type is immediatelyaccessible to the user.
 17. A method for predictive resource accesswithin a technical environment, the method comprising: initiating aresource monitoring engine on a resource procurement profile associatedwith a user; electronically receiving, using the resource monitoringengine, information associated with one or more resources accessed bythe user over a predetermined past period of time; electronicallyreceiving information associated with one or more user characteristicsassociated with the user; initiating one or more machine learningalgorithms on the one or more resources and the information associatedwith one or more user characteristics; generating, using the one or moremachine learning algorithms, a forecasting model configured to predictone or more future resources accessible to the user at a predeterminedfuture time; initiating a resource transformation engine on the one ormore future resources predicted to be accessible to the user at thepredetermined future time; transforming, using the resourcetransformation engine, the one or more future resources predicted to beaccessible to the user at the predetermined future time into one or morealternate resources, wherein the one or more alternate resources areimmediately accessible to the user; and transmitting control signalsconfigured to cause a computing device of the user to display the one ormore alternate resources immediately accessible to the user.
 18. Themethod of claim 17, wherein the method further comprises: electronicallyreceiving, using the resource monitoring engine, the informationassociated with the one or more resources, wherein the informationassociated with the one or more resources comprises at least a resourcetype.
 19. The method of claim 17, wherein the method further comprises:electronically receiving information associated with the one or moreuser characteristics associated with the user, wherein the one or moreuser characteristics comprises at least one or more past resourcetransfers executed by the user, a geographic location of the user, aperiod amount of incoming funds, a periodic amount of outgoing funds,spending behavior, and/or saving behavior.
 20. The method of claim 17,wherein the method further comprises: determining a user authorizationprofile associated with the user, wherein the user authorization profilecomprises at least one or more predetermined authorization profiles; andinitiating the one or more machine learning algorithms on the one ormore resources, the information associated with one or more usercharacteristics, and the user authorization profile.